Toward human-like evaluation for natural language generation with error analysis
The state-of-the-art language model-based automatic metrics, eg BARTScore, benefiting
from large-scale contextualized pre-training, have been successfully used in a wide range of …
from large-scale contextualized pre-training, have been successfully used in a wide range of …
An overview on machine translation evaluation
L Han - arxiv preprint arxiv:2202.11027, 2022 - arxiv.org
Since the 1950s, machine translation (MT) has become one of the important tasks of AI and
development, and has experienced several different periods and stages of development …
development, and has experienced several different periods and stages of development …
Large language models and control mechanisms improve text readability of biomedical abstracts
Biomedical literature often uses complex language and inaccessible professional
terminologies. That is why simplification plays an important role in improving public health …
terminologies. That is why simplification plays an important role in improving public health …
[HTML][HTML] Neural machine translation of clinical text: an empirical investigation into multilingual pre-trained language models and transfer-learning
Clinical text and documents contain very rich information and knowledge in healthcare, and
their processing using state-of-the-art language technology becomes very important for …
their processing using state-of-the-art language technology becomes very important for …
Investigating massive multilingual pre-trained machine translation models for clinical domain via transfer learning
Massively multilingual pre-trained language models (MMPLMs) are developed in recent
years demonstrating superpowers and the pre-knowledge they acquire for downstream …
years demonstrating superpowers and the pre-knowledge they acquire for downstream …
Investigating large language models and control mechanisms to improve text readability of biomedical abstracts
Biomedical literature often uses complex language and inaccessible professional
terminologies. That is why sim-plification plays an important role in improving public health …
terminologies. That is why sim-plification plays an important role in improving public health …
Topic modelling of swedish newspaper articles about coronavirus: a case study using latent dirichlet allocation method
Topic Modelling (TM) is a natural language processing (NLP) method for discovering topics
in a collection of documents. Being an unsupervised method, it is a valuable tool when trying …
in a collection of documents. Being an unsupervised method, it is a valuable tool when trying …
Linguistically-motivated Yorùbá-English machine translation
Translating between languages where certain features are marked morphologically in one
but absent or marked contextually in the other is an important test case for machine …
but absent or marked contextually in the other is an important test case for machine …
Predicting Perfect Quality Segments in MT Output with Fine-Tuned OpenAI LLM: Is it possible to capture editing distance patterns from historical data?
Translation Quality Estimation (TQE) is an important step before deploying the output
translation into usage. TQE is also critical in assessing machine translation (MT) and human …
translation into usage. TQE is also critical in assessing machine translation (MT) and human …
Student's t-Distribution: On Measuring the Inter-Rater Reliability When the Observations are Scarce
In natural language processing (NLP) we always rely on human judgement as the golden
quality evaluation method. However, there has been an ongoing debate on how to better …
quality evaluation method. However, there has been an ongoing debate on how to better …